High-resolution melting analysis after nested PCR for the detection of SARS-CoV-2 spike protein G339D and D796Y variations

Nested PCR effective to detect low viral loads of SARS-CoV-2 in animal samples

SARS-CoV-2 emerged from an animal source and was then transmitted to humans, causing the COVID-19 pandemic. Since a wide range of animals are susceptible to SARS-CoV-2 infection, the zoonotic potential of SARS-CoV-2 increases with every new animal infected. The molecular gold standard assay for SARS-CoV-2 detection is real-time RT-PCR, where the Ct obtained is proportional to the amount of nucleic acid and can be a semi-quantitative measure of the viral load. However, since the use of real-time RT-PCR assays in animal samples is low due to the high costs, the use of validated nested PCR assays will help to monitor large-scale animal samplings, by reducing the costs of detection. In the present study, 140 samples from dogs and cats (15 SARS-CoV-2-positive samples with Ct values from 27 to 33, and 125 negative samples), previously analyzed by real-time RT-PCR, were analyzed by nested PCR. To increase the number of positive samples to determine the sensitivity of the assay, 40 human samples obtained during COVID-19 diagnosis in 2020 were included. The specificity of the primers was analyzed against samples positive to canine coronavirus (CCV) and feline infectious peritonitis virus (FIPV). To calculate the limit of detection (LoD) of the nested PCR, the viral load was estimated extrapolating the Ct value obtained by real-time RT-PCR. The Ct values obtained were considered as semi-quantitative and were able to distinguish between high, moderate and low viral loads. The Kappa value or "agreement" between assays and reliability of the nested PCR were also determined. Eleven of the animal samples analyzed by nested PCR targeting the N gene were detected as positive, while 129 were detected as negative to the virus, with Ct values ranging between17 and 31.5. All the samples from humans analyzed by nested PCR were positive. These results indicate that the assay has a sensitivity of near 95 % and a specificity of 100 %. No unspecific reactions analyzed by nested PCR were observed with the samples positive to CCV and FIPV. The samples detected as positive to SARS-CoV-2 by nested PCR were those that presented a Ct between17 and 31.5. The LoD of the nested PCR was estimated close to 50 copies/µL of viral load, corresponding with a Ct of 31.5. The Kappa value between assays was excellent (k = 0.829). The results obtained demonstrate that nested PCR is useful to detect SARS-CoV-2 low viral loads at a lower cost than with real-time RT-PCR.

L-DNA-Based Melt Analysis Enables Within-Sample Validation of PCR Products

The melt analysis feature in most real-time polymerase chain reaction (PCR) instruments is a simple method for determining if expected or unexpected products are present. High-resolution melt (HRM) analysis seeks to improve the precision of melt temperature measurements for better PCR product sequence characterization. In the area of tuberculosis (TB) drug susceptibility screening, sequencing has shown that a single base change can be sufficient to make a first-line TB drug ineffective. In this study, a reagent-based calibration strategy based on synthetic left-handed (L)-DNA, designated LHRM, was developed to confirm validation of a PCR product with single base resolution. To test this approach, a constant amount of a double-stranded L-DNA melt comparator was added to each sample and used as a within-sample melt standard. The performance of LHRM and standard HRM was used to classify PCR products as drug-susceptible or not drug-susceptible with a test bed of nine synthetic katG variants, each containing single or multiple base mutations that are known to confer resistance to the first-line TB drug isoniazid (INH). LHRM achieved comparable classification to standard HRM relying only on within-sample melt differences between L-DNA and the unknown PCR product. Using a state-of-the-art calibrated instrument and multiple sample classification analysis, standard HRM was performed at 66.7% sensitivity and 98.8% specificity. Single sample analysis incorporating L-DNA for reagent-based calibration into every sample maintained high performance at 77.8% sensitivity and 98.7% specificity. LHRM shows promise as a high-resolution single sample method for validating PCR products in applications where the expected sequence is known.

ICP-MS and fluorescence dual-mode detection of ZIKV-RNA based on quantum dot labeling with hybridization chain reaction

The detection of Zika virus (ZIKV) is of great significance to human life and health. Herein, we presented an ICP-MS and fluorescent dual-mode sensor for quantitative analysis of Zika virus RNA fragments (ZIKV-RNA), which employed quantum dots (QDs) as signal tags and combined with hybridization chain reaction (HCR). The dual-mode sensor realized cross-checking of the analysis results and improved the assay accuracy. Firstly, the single-stranded DNA (ssDNA) was anchored on the surface of magnetic beads (MBs). Afterward, HCR was conducted with probe DNA-CdSe quantum dots conjugates (pDNA-QDs) and link DNA (lDNA), producing the MBs-ssDNA-[pDNA-QDs-lDNA]n conjugates. In the presence of target ZIKV-RNA, a strand displacement reaction occurred, leading to the dissociation of the [pDNA-QDs-lDNA]n labels from the conjugates into the solution. Finally, the signal intensity was detected using ICP-MS and fluorescence analysis, with achieved limits of detection of 131 pM and 152 pM, respectively. The inter-assay RSD values of fluorescence and ICP-MS were 3.94 % and 4.26 % at 10 nM level, respectively, showing that the method had good precision. This method showed high selectivity and was applied to the analysis of biological fluids. There was no significant difference between the results of ICP-MS modes and fluorescence mode. This method offers a new strategy for sensitivity analysis of ZIKV-RNA and exhibits promise in clinical applications for diagnosis.

Rapid monitoring of SARS-CoV-2 variants of concern through high-resolution melt analysis

The current global pandemic of COVID-19 is characterized by waves of infection due to the emergence of new SARS-CoV-2 variants carrying mutations on the Spike (S) protein gene. Since autumn 2020 many Variants of Concern (VOC) have been reported: Alpha/B.1.1.7, Beta/B.1.351, Gamma/P.1, Delta/B.1.617.2, Omicron/B.1.1.529, and sublineages. Surveillance of genomic variants is currently based on whole-genome sequencing (WGS) of viral genomes on a random fraction of samples positive to molecular tests. WGS involves high costs, extended analysis time, specialized staff, and expensive instruments compared to a PCR-based test. To rapidly identify the VOCs in positive samples, six assays based on real-time PCR and high-resolution melting (HRM) were designed on the S gene and applied to 120 oro/nasopharyngeal swab samples collected from October 2020 to June 2022 (106 positive and 14 negative samples). Overall, the assays showed 100% specificity and sensitivity compared with commercial PCR tests for COVID-19. Moreover, 104 samples out of 106 (98.1%) were correctly identified as follows: 8 Wuhan (wild type), 12 Alpha, 23 Delta, 46 Omicron BA.1/BA.1.1, 15 Omicron BA.2/BA.4/BA.5. With our lab equipment, about 10 samples can be processed every 3 h at the cost of less than € 10 ($ 10.60) per sample, including RNA extraction. The implementation of this approach could help local epidemiological surveillance and clinical decision-making.

Potential use of high-resolution melting analyses for SARS-CoV-2 genomic surveillance

The pandemic caused by COVID-19 and the emergence of new variants of SARS-CoV-2 have generated clinical and epidemiological impacts on a global scale. The use of strategies for monitoring viral circulation and identifying mutations in genomic regions involved in host interaction are important measures to mitigate viral dissemination and reduce its likely complications on population health. In this context, the objective of this work was to explore the potential of high-resolution melting (HRM) analysis combined with one-step real-time reverse transcription PCR in a closed-tube system, as a fast and convenient method of screening for SARS-CoV-2 mutations with possible implications on host-pathogen interactions. The HRM analyses allowed the distinction of the Gamma, Zeta, Alpha, Delta, and Omicron variants against the predecessors (B.1.1.28, B.1.1.33) of occurrence in Brazil. It is concluded that the molecular tool standardized here has the potential to optimize the genomic surveillance of SARS-CoV-2, and could be adapted for genomic surveillance of other pathogens, due to its ability to detect, prior to sequencing, samples suggestive of new variants, selecting them more assertively and earlier for whole genome sequencing when compared to random screening.

Machine Learning-Assisted Real-Time Polymerase Chain Reaction and High-Resolution Melt Analysis for SARS-CoV-2 Variant Identification

Since the declaration of COVID-19 as a pandemic in early 2020, multiple variants of the severe acute respiratory syndrome-related coronavirus (SARS-CoV-2) have been detected. The emergence of multiple variants has raised concerns due to their impact on public health. Therefore, it is crucial to distinguish between different viral variants. Here, we developed a machine learning web-based application for SARS-CoV-2 variant identification via duplex real-time polymerase chain reaction (PCR) coupled with high-resolution melt (qPCR-HRM) analysis. As a proof-of-concept, we investigated the platform's ability to identify the Alpha, Delta, and wild-type strains using two sets of primers. The duplex qPCR-HRM could identify the two variants reliably in as low as 100 copies/μL. Finally, the platform was validated with 167 nasopharyngeal swab samples, which gave a sensitivity of 95.2%. This work demonstrates the potential for use as automated, cost-effective, and large-scale viral variant surveillance.

An Update on Detection Technologies for SARS-CoV-2 Variants of Concern

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is responsible for the global epidemic of Coronavirus Disease 2019 (COVID-19), with a significant impact on the global economy and human safety. Reverse transcription-quantitative polymerase chain reaction (RT-PCR) is the gold standard for detecting SARS-CoV-2, but because the virus's genome is prone to mutations, the effectiveness of vaccines and the sensitivity of detection methods are declining. Variants of concern (VOCs) include Alpha, Beta, Gamma, Delta, and Omicron, which are able to evade recognition by host immune mechanisms leading to increased transmissibility, morbidity, and mortality of COVID-19. A range of research has been reported on detection techniques for VOCs, which is beneficial to prevent the rapid spread of the epidemic, improve the effectiveness of public health and social measures, and reduce the harm to human health and safety. However, a meaningful translation of this that reduces the burden of disease, and delivers a clear and cohesive message to guide daily clinical practice, remains preliminary. Herein, we summarize the capabilities of various nucleic acid and protein-based detection methods developed for VOCs in identifying and differentiating current VOCs and compare the advantages and disadvantages of each method, providing a basis for the rapid detection of VOCs strains and their future variants and the adoption of corresponding preventive and control measures.

High-resolution melting analysis to discriminate between the SARS-CoV-2 Omicron variants BA.1 and BA.2

High-resolution melting (HRM) analysis was conducted to discriminate between SARS-CoV-2 Omicron variant BA.1 (B.1.1.529.1) and subvariant BA.2 (B.1.1.529.2). We performed two-step PCR consisting of the first PCR and the second nested PCR to prepare the amplicon for HRM analysis, which detected G339D, N440K, G446S and D796Y variations in the SARS-CoV-2 spike protein. The melting temperatures (Tms) of the amplicons from the cDNA of the Omicron variant BA.1 and subvariant BA.2 receptor binding domain (RBD) in spike protein were the same: 75.2 °C (G339D variation) and 73.4 °C (D796Y variation). These Tms were distinct from those of SARS-CoV-2 isolate Wuhan-Hu-1, and were specific to the Omicron variant. In HRM analyses that detected the N440K and G446S variations, the Tms of amplicons from the cDNA of the Omicron variant BA.1 and subvariant BA.2 RBDs were 73.0 °C (N440K and G446S variations) and 73.5 °C (G446S variation). This difference indicates that the SARS-CoV-2 Omicron variants BA.1 and BA.2 can be clearly discriminated. Our study demonstrates the usefulness of HRM analysis after two-step PCR for the discrimination of SARS-CoV-2 variants.